A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a complication that can occur late in pregnancy. Preeclampsia is a sudden ...

A new computational method allows modern atomic models to learn from experimental thermodynamic data, according to a ...

Future 6G wireless networks will not only transmit data but will also be able to sense and understand their surrounding environment using the same radio signals. This PhD project will develop new ...

This studentship will develop physics-informed Edge AI methods for predictive health management of batteries and power electronics in electrified vehicles under real-world driving conditions.

As electric and autonomous vehicles take on more driving tasks, understanding exactly how a car behaves at any given moment ...

Heart failure is a leading cause of hospitalization and long-term disability, with many individuals progressing from subclinical disease to overt symptoms ...

A team of EPFL researchers has developed an AI algorithm capable of modelling complex dynamical processes while adhering to the laws of physics—specifically Newton’s third law.

A team of EPFL researchers has developed an AI algorithm that can model complex dynamical processes while taking into account the laws of physics—using Newton's third law. Their research is published ...

Based on these challenges, a comprehensive reassessment of how AI should be deployed in electrocatalysis has become urgently needed. Addressing this need, a review published (DOI: 10.1016/j.esci.2025.

Electra announces a major milestone with the successful validation of its EVE‑Ai™ Adaptive Controls platform, enabling ...

Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has ...

Accurate joint kinematics estimation is essential for understanding human movement and supporting biomechanical applications. Although optical motion capture systems are accurate, their high cost, ...